Yejun Gu

590 total citations
23 papers, 437 citations indexed

About

Yejun Gu is a scholar working on Materials Chemistry, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Yejun Gu has authored 23 papers receiving a total of 437 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Materials Chemistry, 12 papers in Mechanical Engineering and 6 papers in Mechanics of Materials. Recurrent topics in Yejun Gu's work include Microstructure and mechanical properties (20 papers), Hydrogen embrittlement and corrosion behaviors in metals (6 papers) and Fusion materials and technologies (5 papers). Yejun Gu is often cited by papers focused on Microstructure and mechanical properties (20 papers), Hydrogen embrittlement and corrosion behaviors in metals (6 papers) and Fusion materials and technologies (5 papers). Yejun Gu collaborates with scholars based in United States, Hong Kong and Singapore. Yejun Gu's co-authors include Jaafar A. El‐Awady, Yang Xiang, David J. Srolovitz, S.S. Quek, Laurent Capolungo, Sean R. Agnew, Rodney J. McCabe, Fulin Wang, Shuyang Dai and Yichao Zhu and has published in prestigious journals such as Science, SHILAP Revista de lepidopterología and Acta Materialia.

In The Last Decade

Yejun Gu

21 papers receiving 427 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yejun Gu United States 12 314 276 113 77 63 23 437
Linlin Li China 10 341 1.1× 448 1.6× 157 1.4× 65 0.8× 85 1.3× 15 547
B.P. Eftink United States 12 558 1.8× 489 1.8× 178 1.6× 61 0.8× 104 1.7× 27 716
Anxin Ma Germany 13 414 1.3× 434 1.6× 283 2.5× 52 0.7× 94 1.5× 24 603
A. Yilmaz Türkiye 8 288 0.9× 253 0.9× 103 0.9× 140 1.8× 95 1.5× 18 446
Chuanshi Hong Denmark 10 396 1.3× 357 1.3× 161 1.4× 40 0.5× 69 1.1× 23 492
Inga G. Ringdalen Norway 13 354 1.1× 304 1.1× 111 1.0× 34 0.4× 191 3.0× 27 478
David M. Norfleet United States 6 531 1.7× 278 1.0× 168 1.5× 38 0.5× 34 0.5× 11 620
Su Leen Wong United States 9 457 1.5× 560 2.0× 263 2.3× 83 1.1× 105 1.7× 11 678
Florian Kauffmann Germany 9 268 0.9× 305 1.1× 157 1.4× 31 0.4× 36 0.6× 19 392
Krzysztof Wieczerzak Poland 12 337 1.1× 466 1.7× 123 1.1× 49 0.6× 99 1.6× 34 556

Countries citing papers authored by Yejun Gu

Since Specialization
Citations

This map shows the geographic impact of Yejun Gu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yejun Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yejun Gu more than expected).

Fields of papers citing papers by Yejun Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yejun Gu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yejun Gu. The network helps show where Yejun Gu may publish in the future.

Co-authorship network of co-authors of Yejun Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Yejun Gu. A scholar is included among the top collaborators of Yejun Gu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yejun Gu. Yejun Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Luo, Jing, Yejun Gu, Yanfei Wang, Xiaolong Ma, & Jaafar A. El‐Awady. (2025). Uncertainty-aware machine learning framework for predicting dislocation plasticity and stress–strain response in metallic alloys, Part I : FCC systems. Acta Materialia. 302. 121610–121610.
2.
Dai, Shuyang, et al.. (2023). A continuum model for dislocation climb. International Journal of Plasticity. 168. 103700–103700. 2 indexed citations
3.
4.
Gu, Yejun, et al.. (2023). A statistical perspective for predicting the strength of metals: Revisiting the Hall–Petch relationship using machine learning. Acta Materialia. 266. 119631–119631. 13 indexed citations
5.
Gu, Yejun, Zhi Li, & Huajian Gao. (2023). Hetero-Boundary-Affected Regions in Heterostructured Materials. JOM. 75(5). 1405–1422. 3 indexed citations
6.
Zhang, Yin, Yejun Gu, Wen Chen, et al.. (2022). Modeling of microscale internal stresses in additively manufactured stainless steel. Modelling and Simulation in Materials Science and Engineering. 30(7). 74001–74001. 17 indexed citations
7.
Birnbaum, Andrew J., et al.. (2022). The interplay of local chemistry and plasticity in controlling microstructure formation during laser powder bed fusion of metals. Additive manufacturing. 55. 102791–102791. 15 indexed citations
8.
Gu, Yejun, et al.. (2022). Effects of pre-stress on the mechanical properties and microstructure of neutron-irradiated high-purity aluminum. Journal of Nuclear Materials. 573. 154126–154126. 2 indexed citations
9.
Singh, Saransh, et al.. (2020). Scanning transmission electron microscopy image simulations of complex dislocation structures generated by discrete dislocation dynamics. Ultramicroscopy. 219. 113124–113124. 2 indexed citations
10.
Gu, Yejun, Jean‐Charles Stinville, Patrick G. Callahan, et al.. (2020). Slip delocalization and diffusion mediated carbide formation during fatigue of a nickel-base superalloy. International Journal of Fatigue. 145. 106077–106077. 2 indexed citations
11.
Gu, Yejun, et al.. (2020). The heterogeneity of persistent slip band nucleation and evolution in metals at the micrometer scale. Science. 370(6513). 95 indexed citations
12.
Gu, Yejun, et al.. (2020). A statistical model for predicting size effects on the yield strength in dislocation-mediated crystal plasticity. Journal of the Mechanics and Physics of Solids. 147. 104245–104245. 10 indexed citations
13.
Rafiei, Mohammad Hossein, Yejun Gu, & Jaafar A. El‐Awady. (2020). Machine Learning of Dislocation-Induced Stress Fields and Interaction Forces. JOM. 72(12). 4380–4392. 5 indexed citations
14.
Wang, Fulin, Yejun Gu, Rodney J. McCabe, et al.. (2020). 〈 c + a 〉 dislocations in { 10 1 ¯ 2 } twins in Mg: A kinematic and energetic requirement. Acta Materialia. 195. 13–24. 29 indexed citations
15.
Gu, Yejun, et al.. (2019). Dislocation dynamics formulation for self-climb of dislocation loops by vacancy pipe diffusion. International Journal of Plasticity. 120. 262–277. 17 indexed citations
16.
Gu, Yejun, Yang Xiang, David J. Srolovitz, & Jaafar A. El‐Awady. (2018). Self-healing of low angle grain boundaries by vacancy diffusion and dislocation climb. Scripta Materialia. 155. 155–159. 20 indexed citations
17.
Gu, Yejun, Jian Han, Shuyang Dai, et al.. (2017). Point defect sink efficiency of low-angle tilt grain boundaries. Journal of the Mechanics and Physics of Solids. 101. 166–179. 18 indexed citations
18.
Gu, Yejun, et al.. (2016). Energy of low angle grain boundaries based on continuum dislocation structure. Acta Materialia. 126. 11–24. 46 indexed citations
19.
Gu, Yejun, Yang Xiang, S.S. Quek, & David J. Srolovitz. (2015). Three-dimensional formulation of dislocation climb. Journal of the Mechanics and Physics of Solids. 83. 319–337. 47 indexed citations
20.
Gu, Yejun, Yang Xiang, & David J. Srolovitz. (2015). Relaxation of low-angle grain boundary structure by climb of the constituent dislocations. Scripta Materialia. 114. 35–40. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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